文章摘要
王莉娜,Zhang Zuofeng.孟德尔随机化法在因果推断中的应用[J].中华流行病学杂志,2017,38(4):547-552
孟德尔随机化法在因果推断中的应用
Mendelian randomization approach, used for causal inferences
投稿时间:2016-12-14  
DOI:10.3760/cma.j.issn.0254-6450.2017.04.027
中文关键词: 孟德尔随机化;工具变量;因果推断;全基因组关联研究
英文关键词: Mendelian randomization;Instrumental Variable;Causal inferences;GWAS
基金项目:国家自然科学基金(81673259);江苏省自然科学基金(BK20161435)
作者单位E-mail
王莉娜 210009 南京, 东 南大学公共卫生学院流行病与卫生统计学系  
Zhang Zuofeng 90095洛杉矶, 加州大学洛杉矶分校公共卫生学院流行病学系 zfzhang@ucla.edu 
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中文摘要:
      孟德尔随机化(Mendelian Randomization,MR)研究设计,遵循“亲代等位基因随机分配给子代”的孟德尔遗传规律,如果基因型决定表型,基因型通过表型而与疾病发生关联,因此可以使用基因型作为工具变量来推断表型与疾病之间的关联。近年来,MR的研究设计随着统计学方法、大样本GWAS数据、表观遗传学以及各种“组学”技术的不断发展,在探讨复杂暴露因素与疾病结局因果关联中应用日益广泛。本文对近年来出现的MR研究设计策略、可靠性评价及局限性进行介绍。
英文摘要:
      Mendelian randomization (MR) approach is based on the Mendelian genetic law,which is called “Parental alleles that randomly assigned to the offspring”. MR refers to the use of genetic variants to develop causal inferences from observational data, if the variant genotype is associated with the phenotype and the variant genotype associated with the risk of disease of interest through the phenotype. Hence, the genotype can be used as Instrumental Variable (IV) to infer the causal relation between the phenotype and the risk of diseases. In recent years, MR approach is widely used in causal inference between the exposure factors and the risks of disease, along with the rapid development of statistical methods, big datasets of GWAS, epigenetics and the various “omics” techniques. This paper provides an overview of the MR strategies and addresses the related assumptions and implications, with reliability and limitations included.
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